Instructions to use nitrosocke/redshift-diffusion-768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/redshift-diffusion-768 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/redshift-diffusion-768", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Training method used for training sd2 model to make this model and related model on your hub
#10
by Ambesh - opened
Hey @nitrosocke ,
Kudos for the redshift model, also for the others.
I am curios, on how were you able to transfer the concept to this model,
I want to know which training framework you used to make this model.
Was it DreamBooth, textual-inversion or any other I have no knowledge about?
Please give us some reference on this.
I used a slightly modified version of Shivams Dreambooth script for this model. you can try it out yourself here for example:
https://colab.research.google.com/drive/1S0GzxAlL_8-qGQspLKrLSSaNeAzZrgMF